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Publications [Citations][Software]
| Manuscripts |
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Mei, T., Fan, Y. and Lv, J. (2024). Exogenous randomness empowering random forests . Manuscript. [PDF]
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Huang, J., Du, Y., Kelly, K. R., Fan, Y., Lv, J., Zhong, J. F. and Sun, F. (2024). DeepDeconUQ estimates malignant cell fraction prediction intervals in bulk RNA-seq tissue . Manuscript. [PDF]
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Fan, Y., Gao, L. and Lv, J. (2024). ARK: robust knockoffs inference with coupling . Manuscript. [PDF]
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Zheng, Z., Zhou, X., Fan, Y. and Lv, J. (2024). SOFARI: high-dimensional manifold-based inference . Manuscript. [PDF]
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Zuo, W., Zhu, Z., Du, Y., Yeh, Y.-C., Fuhrman, J. A., Lv, J., Fan, Y. and Sun, F. (2024). DeepLINK-T: deep learning inference for time series data using knockoffs and LSTM . Manuscript. [PDF]
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Huo, Y., Fan, Y. and Han, F. (2024). On the adaptation of causal forests to manifold data . Manuscript. [PDF]
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Fan, J., Fan, Y., Lv, J. and Yang, F. (2024). SIMPLE-RC: group network inference with non-sharp nulls and weak signals . Manuscript. [PDF]
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Chi, C.-M., Fan, Y. and Lv, J. (2024). FACT: high-dimensional multi-output random forests inference . Manuscript. [PDF]
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Derenski, J., Fan, Y., James, G. and Xu, M. (2024). An empirical Bayes shrinkage method for functional data . Manuscript. [PDF]
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| 2024 |
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Demirkaya, E., Fan, Y., Gao, L., Lv, J., Vossler, P. and Wang, J. (2024).
Optimal nonparametric inference with two-scale distributional nearest neighbors.
Journal of the American Statistical Association 119, 297-307. [PDF] [Supplementary Material]
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Chi, C.-M., Fan, Y., Ing, C.-K. and Lv, J. (2024).
High-dimensional knockoffs inference for time series data.
Journal of the American Statistical Association, to appear. [PDF]
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| 2023 |
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Han, X., Yang, Q. and Fan, Y. (2023).
Universal rank inference via residual subsampling with application to large networks.
The Annals of Statistics 51, 1109–1133. [PDF]
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Han, X., Tong, X. and Fan, Y. (2023).
Eigen selection in spectral clustering: a theory guided practice.
Journal of the American Statistical Association 118, 109–121. [PDF] [Supplementary Material]
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| 2022 |
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Chi, C.-M., Vossler, P., Fan, Y. and Lv, J. (2022).
Asymptotic properties of high-dimensional random forests.
The Annals of Statistics 50, 3415-3438. [PDF]
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Fan, J., Fan, Y., Han, X. and Lv, J. (2022).
SIMPLE: statistical inference on membership profiles in large networks.
Journal of the Royal Statistical Society Series B 84, 630-653. [PDF] [Supplementary Material]
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Cannings, T. I. and Fan, Y. (2022).
The correlation-assisted missing data estimator.
Journal of Machine Learning Research 23, 1-49. [PDF]
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Fan, J., Fan, Y., Han, X. and Lv, J. (2022).
Asymptotic theory of eigenvectors for random matrices with diverging spikes.
Journal of the American Statistical Association 117, 996-1009. [PDF] [Supplementary Material]
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Li, D., Kong, Y., Fan, Y. and Lv, J. (2022).
High-dimensional interaction detection with false sign rate control.
Journal of Business & Economic Statistics 40, 1234-1245. [PDF] [Supplementary Material]
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| 2021 |
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Zhu, Z., Fan, Y., Kong, Y., Lv, J. and Sun, F. (2021).
DeepLINK: deep learning inference using knockoffs with applications to genomics.
Proceedings of the National Academy of Sciences of the United States of America 118, e2104683118. [PDF]
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Gao, L., Fan, Y., Lv, J. and Shao, Q. (2021).
Asymptotic distributions of high-dimensional distance correlation inference.
The Annals of Statistics 49, 1999-2020. [PDF] [Supplementary Material]
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Bai, X., Ren, J., Fan, Y. and Sun, F. (2021).
KIMI: knockoff inference for motif identification from molecular sequences with controlled false discovery rate.
Bioinformatics 37, 759-766. [PDF]
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| 2020 |
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Fan, Y., Demirkaya, E., Li, G. and Lv, J. (2020).
RANK: large-scale inference with graphical nonlinear knockoffs.
Journal of the American Statistical Association 115, 362-379. [PDF] [Supplementary Material]
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Cannings, T. I., Fan, Y. and Samworth, R. J. (2020).
Classification with imperfect training labels.
Biometrika 107, 311-330. [PDF] [Supplementary Material]
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Fan, Y., Lv, J., Sharifvaghefi, M. and Uematsu, Y. (2020).
IPAD: stable interpretable forecasting with knockoffs inference.
Journal of the American Statistical Association 115, 1822-1834. [PDF] [Supplementary Material]
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Tang, C., Fan, Y. and Kong, Y. (2020).
Precision matrix estimation by inverse principal orthogonal decomposition.
Communications in Mathematical Research 36, 68-92. [PDF]
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Wu, H., Fan, Y. and Lv, J. (2020).
Statistical insights into deep neural network learning in subspace classification.
Stat 9, e273. [PDF]
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| 2019 |
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Fan, Y., Demirkaya, E. and Lv, J. (2019).
Nonuniformity of p-values can occur early in diverging dimensions.
Journal of Machine Learning Research 20, 1-33. [PDF]
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Ren, Z., Kang, Y., Fan, Y. and Lv, J. (2019).
Tuning-free heterogeneous inference in massive networks.
Journal of the American Statistical Association 114, 1908-1925. [PDF] [Supplementary Material]
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Uematsu, Y., Fan, Y., Chen, K., Lv, J. and Lin, W. (2019).
SOFAR: large-scale association network learning.
IEEE Transactions on Information Theory 65, 4924-4939. [PDF] [Supplementary Material]
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| 2018 |
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Candès, E. J., Fan, Y., Janson, L. and Lv, J. (2018).
Panning for gold: 'model-X' knockoffs for high dimensional controlled variable selection.
Journal of the Royal Statistical Society Series B 80, 551-577. [PDF] [Supplementary Material]
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Lu, Y., Fan, Y., Lv, J. and Noble, W. S. (2018).
DeepPINK: reproducible feature selection in deep neural networks.
Advances in Neural Information Processing Systems (NeurIPS 2018). [PDF]
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| 2017 |
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Kong, Y., Li, D., Fan, Y. and Lv, J. (2017).
Interaction pursuit in high-dimensional multi-response regression via distance correlation.
The Annals of Statistics 45, 897-922. [PDF] [Supplementary Material]
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Derenski, J., Fan, Y. and James, G. (2017).
Discussion of "Random-projection ensemble classification."
Journal of the Royal Statistical Society Series B 79, 1009-1010. [PDF]
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| 2016 |
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Fan, Y. and Lv, J. (2016).
Innovated scalable efficient estimation in ultra-large Gaussian graphical models.
The Annals of Statistics 44, 2098-2126. [PDF] [Supplementary Material]
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| 2015 |
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Fan, Y., Kong, Y., Li, D. and Zheng, Z. (2015).
Innovated interaction screening for high-dimensional nonlinear classification.
The Annals of Statistics 43, 1243-1272. [PDF] [Supplementary Material]
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Bahadori, M. T., Kale, D., Fan, Y. and Liu, Y. (2015).
Functional subspace clustering with application to time series.
International Conference on Machine Learning (ICML'15). [PDF]
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Fan, Y., James, G. and Radchenko, P. (2015).
Functional additive regression.
The Annals of Statistics 43, 2296-2325. [PDF] [Supplementary Material]
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| 2014 |
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Fan, Y. and Lv, J. (2014).
Asymptotic properties for combined L1 and concave regularization.
Biometrika 101, 57-70. [PDF]
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Fan, J., Fan, Y. and Barut, E. (2014).
Adaptive robust variable selection.
The Annals of Statistics 42, 324-351. [PDF] [Supplementary Material]
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Zheng, Z., Fan, Y. and Lv, J. (2014).
High dimensional thresholded regression and shrinkage effect.
Journal of the Royal Statistical Society Series B 76, 627-649. [PDF]
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Fan, Y., Foutz, N., James, G. and Jank, W. (2014).
Functional response additive model estimation with online virtual stock markets.
The Annals of Applied Statistics 8, 2435-2460. [PDF]
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| 2013 |
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Fan, Y., Jin, J. and Yao, Z. (2013).
Optimal classification in sparse Gaussian graphic model.
The Annals of Statistics 41, 2537-2571. [PDF] [Supplementary Material]
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Fan, Y. and Lv, J. (2013).
Asymptotic equivalence of regularization methods in thresholded parameter space.
Journal of the American Statistical Association 108, 1044-1061. [PDF]
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Fan, Y. and Tang, C. (2013).
Tuning parameter selection in high dimensional penalized likelihood.
Journal of the Royal Statistical Society Series B 75, 531-552. [PDF]
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Tang, C. and Fan, Y. (2013).
Discussion of "Large covariance estimation by thresholding principal orthogonal complements".
Journal of the Royal Statistical Society Series B 75, 671. [PDF]
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| 2012 |
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Fan, Y. and Li, R. (2012).
Variable selection in linear mixed effects models.
The Annals of Statistics 40, 2043-2068. [PDF]
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| 2011 |
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Fan, Y. and Fan, J. (2011).
Testing and detecting jumps based on a discretely observed process.
Journal of Econometrics 164, 331-344. [PDF]
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| 2010 |
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Jiang, J., Fan, Y. and Fan, J. (2010).
Estimation in additive models with highly or non-highly correlated covariates.
The Annals of Statistics 38, 1403-1432. [PDF]
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Fan, J., Fan, Y. and Wu, Y. (2010).
High dimensional classification.
High-dimensional Statistical Inference (T. T. Cai and X. Shen, eds.), 3-37. World Scientific, New Jersey. [PDF]
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| 2009 |
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Lv, J. and Fan, Y. (2009).
A unified approach to model selection and sparse recovery using regularized least squares.
The Annals of Statistics 37, 3498-3528. [PDF]
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| 2008 |
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Fan, J. and Fan, Y. (2008).
High-dimensional classification using features annealed independence rules.
The Annals of Statistics 36, 2605-2637. [PDF]
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Fan, J., Fan, Y. and Lv, J. (2008).
High dimensional covariance matrix estimation using a factor model.
Journal of Econometrics 147, 186-197. [PDF]
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| 2007 |
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Fan, J., Fan, Y. and Jiang, J. (2007).
Dynamic integration of time- and state-domain methods for volatility estimation.
Journal of the American Statistical Association 102, 618-631. [PDF]
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Fan, J., Fan, Y. and Lv, J. (2007).
Aggregation of nonparametric estimators for volatility matrix.
Journal of Financial Econometrics 5, 321-357. [PDF]
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| 2006 |
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Fan, J. and Fan, Y. (2006).
Comment on "Quantile autoregression".
Journal of the American Statistical Association 101, 991-994. [PDF]
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